Numerical simulation of extreme waves during the storm of 20–22 January 2000 using winds generated by the CMC weather prediction model
Bibliographic record
Abstract
Abstract The storm of 20–22 January 2000 over Canada's Atlantic Provinces was an exceptional storm for several reasons, these include extremely high coastal ocean waves, widespread coastal damage due to the storm surge, very strong winds over a large area, an extremely fast deepening rate, and a very low central pressure. It produced unusually large waves which caused significant damage in communities along the south coast of Newfoundland and the eastern shores of Nova Scotia. Bottom scouring was observed around the feet of three mobile offshore oil and gas drilling platforms operating near Sable Island. Using buoy data enhanced with a detailed data set from one of the platforms, this study examines the growth of destructive waves and the performance of two state‐of‐the‐art third generation ocean wave models running in shallow water mode. The wave models perform well in numerically simulating the extreme waves associated with this storm. They correctly predict the growth of wind waves and handle the arrival of long‐period swells well. Unprecedented waves that damaged buildings and a lighthouse in the Channel Head area of Port‐Aux‐Basques retained most of their deep‐water energy until they were less than one wavelength from the beach. Computations show that dynamic (or trapped) fetch was not a contributing factor in the generation of the observed extreme sea states although the long‐period swells were supported by winds for a significant part of their transit northward. However, it appears that the model‐generated enhanced wave growth at the buoy location just off the southwestern coast of Newfoundland may be partially linked to the creation of model trapped fetch. The January 2000 storm was indeed an extreme storm and was the most intense non‐tropical storm to form over Atlantic Canada in decades.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".